| Conditional random fields as recurrent neural networks S Zheng, S Jayasumana, B Romera-Paredes, V Vineet, Z Su, D Du, ... Proceedings of the IEEE international conference on computer vision, 1529-1537, 2015 | 2227 | 2015 |
| Clinically applicable deep learning for diagnosis and referral in retinal disease J De Fauw, JR Ledsam, B Romera-Paredes, S Nikolov, N Tomasev, ... Nature medicine 24 (9), 1342-1350, 2018 | 821 | 2018 |
| An embarrassingly simple approach to zero-shot learning B Romera-Paredes, P Torr International Conference on Machine Learning, 2152-2161, 2015 | 711 | 2015 |
| International evaluation of an AI system for breast cancer screening SM McKinney, M Sieniek, V Godbole, J Godwin, N Antropova, H Ashrafian, ... Nature 577 (7788), 89-94, 2020 | 344 | 2020 |
| Recurrent instance segmentation B Romera-Paredes, PHS Torr European conference on computer vision, 312-329, 2016 | 261 | 2016 |
| Sparse coding for multitask and transfer learning A Maurer, M Pontil, B Romera-Paredes International conference on machine learning, 343-351, 2013 | 162 | 2013 |
| Multilinear multitask learning B Romera-Paredes, H Aung, N Bianchi-Berthouze, M Pontil International Conference on Machine Learning, 1444-1452, 2013 | 160 | 2013 |
| A probabilistic u-net for segmentation of ambiguous images S Kohl, B Romera-Paredes, C Meyer, J De Fauw, JR Ledsam, ... Advances in neural information processing systems, 6965-6975, 2018 | 153 | 2018 |
| A new convex relaxation for tensor completion B Romera-Paredes, M Pontil Advances in Neural Information Processing Systems 26, 2967-2975, 2013 | 134 | 2013 |
| The benefit of multitask representation learning A Maurer, M Pontil, B Romera-Paredes The Journal of Machine Learning Research 17 (1), 2853-2884, 2016 | 131 | 2016 |
| Exploiting unrelated tasks in multi-task learning BR Paredes, A Argyriou, N Berthouze, M Pontil Artificial intelligence and statistics, 951-959, 2012 | 106 | 2012 |
| The automatic detection of chronic pain-related expression: requirements, challenges and the multimodal EmoPain dataset MSH Aung, S Kaltwang, B Romera-Paredes, B Martinez, A Singh, M Cella, ... IEEE transactions on affective computing 7 (4), 435-451, 2015 | 104 | 2015 |
| Deep learning to achieve clinically applicable segmentation of head and neck anatomy for radiotherapy S Nikolov, S Blackwell, R Mendes, J De Fauw, C Meyer, C Hughes, ... arXiv preprint arXiv:1809.04430, 2018 | 95 | 2018 |
| Conditional random fields meet deep neural networks for semantic segmentation: Combining probabilistic graphical models with deep learning for structured prediction A Arnab, S Zheng, S Jayasumana, B Romera-Paredes, M Larsson, ... IEEE Signal Processing Magazine 35 (1), 37-52, 2018 | 71 | 2018 |
| Emotion recognition by two view SVM_2K classifier on dynamic facial expression features H Meng, B Romera-Paredes, N Bianchi-Berthouze Face and Gesture 2011, 854-859, 2011 | 49 | 2011 |
| Laughter type recognition from whole body motion HJ Griffin, MSH Aung, B Romera-Paredes, C McLoughlin, G McKeown, ... 2013 Humaine Association Conference on Affective Computing and Intelligent …, 2013 | 48 | 2013 |
| Facial expression tracking C Zhang, Z Zhang, BR PAREDES US Patent 9,672,416, 2017 | 47 | 2017 |
| A One-Vs-One Classifier Ensemble With Majority Voting for Activity Recognition. B Romera-Paredes, MSH Aung, N Bianchi-Berthouze ESANN, 2013 | 47 | 2013 |
| Facial expression tracking from head-mounted, partially observing cameras B Romera-Paredes, C Zhang, Z Zhang 2014 IEEE International Conference on Multimedia and Expo (ICME), 1-6, 2014 | 36 | 2014 |
| Transfer learning to account for idiosyncrasy in face and body expressions B Romera-Paredes, MSH Aung, M Pontil, N Bianchi-Berthouze, ... 2013 10th IEEE International Conference and Workshops on Automatic Face and …, 2013 | 30 | 2013 |
Nadia Bianchi-BerthouzeProfessor Affective Computing and Interaction, University College LondonVerified email at ucl.ac.uk
